use sets for membership checks

fix typos

.pre-commit-config.yaml

@@ -1,8 +1,7 @@
-exclude: ^(docs|test_files|tests)
+exclude: ^(docs|test_files)
 
 ci:
   autoupdate_schedule: monthly
-  skip: [mypy]
   autofix_commit_msg: pre-commit auto-fixes
   autoupdate_commit_msg: pre-commit autoupdate
 
@@ -23,7 +22,7 @@ repos:
       - id: trailing-whitespace
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.6.1
+    rev: v1.7.0
     hooks:
       - id: mypy
         additional_dependencies: [types-requests]

custodian/cli/run_vasp.py

@@ -77,11 +77,18 @@ def get_jobs(args):
             from pymatgen.io.vasp.sets import MPStaticDielectricDFPTVaspInputSet, MPStaticSet
 
             # vis = MPStaticSet.from_prev_calc(
-            #     ".", user_incar_settings={"EDIFF": 1e-6, "IBRION": 8,
-            #                               "LEPSILON": True, 'LREAL':False,
-            #                               "LPEAD": True, "ISMEAR": 0,
-            #                               "SIGMA": 0.01},
-            #     ediff_per_atom=False)
+            #     ".",
+            #     user_incar_settings={
+            #         "EDIFF": 1e-6,
+            #         "IBRION": 8,
+            #         "LEPSILON": True,
+            #         "LREAL": False,
+            #         "LPEAD": True,
+            #         "ISMEAR": 0,
+            #         "SIGMA": 0.01,
+            #     },
+            #     ediff_per_atom=False,
+            # )
             vis = MPStaticDielectricDFPTVaspInputSet()
             incar = vis.get_incar(vinput["POSCAR"].structure)
             unset = {}

custodian/cp2k/handlers.py

@@ -112,8 +112,8 @@ class UnconvergedScfErrorHandler(ErrorHandler):
                 can also use Iterative Refinement of the approximate congruency
                 transformation.
             (iv) Once can enable rotations of the occupied subspace which allows
-                 fractional occupations with  OT. As of October 2021, this option cannot
-                 be used with 3 point CG, FULL_ALL, or FULL_SINGLE_INVERSE.
+                fractional occupations with  OT. As of October 2021, this option cannot
+                be used with 3 point CG, FULL_ALL, or FULL_SINGLE_INVERSE.
 
     (2) Traditional Diagonalization:
 

custodian/cp2k/jobs.py

@@ -195,8 +195,8 @@ def gga_static_to_hybrid(
         )
 
         ci = Cp2kInput.from_file(zpath(input_file))
-        r = ci["global"].get("run_type", Keyword("RUN_TYPE", "ENERGY_FORCE")).values[0]
-        if r in ["ENERGY", "WAVEFUNCTION_OPTIMIZATION", "WFN_OPT", "ENERGY_FORCE"]:  # no need for double job
+        run_type = ci["global"].get("run_type", Keyword("RUN_TYPE", "ENERGY_FORCE")).values[0]
+        if run_type in {"ENERGY", "WAVEFUNCTION_OPTIMIZATION", "WFN_OPT", "ENERGY_FORCE"}:  # no need for double job
             return [job1]
 
         job2_settings_override = [
@@ -217,7 +217,7 @@ def gga_static_to_hybrid(
                                 "WFN_RESTART_FILE_NAME": "GGA-RESTART.wfn",
                             }
                         },
-                        "GLOBAL": {"RUN_TYPE": r},
+                        "GLOBAL": {"RUN_TYPE": run_type},
                     },
                 },
             }
@@ -257,8 +257,8 @@ def double_job(
             settings_override={},
         )
         ci = Cp2kInput.from_file(zpath(input_file))
-        r = ci["global"].get("run_type", Keyword("RUN_TYPE", "ENERGY_FORCE")).values[0]
-        if r not in ["ENERGY", "WAVEFUNCTION_OPTIMIZATION", "WFN_OPT"]:
+        run_type = ci["global"].get("run_type", Keyword("RUN_TYPE", "ENERGY_FORCE")).values[0]
+        if run_type not in {"ENERGY", "WAVEFUNCTION_OPTIMIZATION", "WFN_OPT"}:
             job1.settings_override = [
                 {"dict": input_file, "action": {"_set": {"GLOBAL": {"RUN_TYPE": "ENERGY_FORCE"}}}}
             ]
@@ -273,7 +273,7 @@ def double_job(
             suffix="2",
             restart=True,
         )
-        job2.settings_override = [{"dict": input_file, "action": {"_set": {"GLOBAL": {"RUN_TYPE": r}}}}]
+        job2.settings_override = [{"dict": input_file, "action": {"_set": {"GLOBAL": {"RUN_TYPE": run_type}}}}]
 
         return [job1, job2]
 
@@ -321,7 +321,7 @@ def pre_screen_hybrid(
 
         ci = Cp2kInput.from_file(zpath(input_file))
         r = ci["global"].get("run_type", Keyword("RUN_TYPE", "ENERGY_FORCE")).values[0]
-        if r in ["ENERGY", "WAVEFUNCTION_OPTIMIZATION", "WFN_OPT", "ENERGY_FORCE"]:  # no need for double job
+        if r in {"ENERGY", "WAVEFUNCTION_OPTIMIZATION", "WFN_OPT", "ENERGY_FORCE"}:  # no need for double job
             return [job1]
 
         job2_settings_override = [

custodian/qchem/jobs.py

@@ -320,7 +320,7 @@ def opt_with_frequency_flattener(
                     opt_geom_opt = copy.deepcopy(opt_indata.geom_opt)
                     opt_geom_opt["initial_hessian"] = "read"
                 for key in opt_indata.rem:
-                    if key not in ["job_type", "geom_opt2", "scf_guess_always"]:
+                    if key not in {"job_type", "geom_opt2", "scf_guess_always"}:
                         if freq_rem.get(key, None) != opt_indata.rem[key] and "geom_opt" not in key:
                             freq_rem[key] = opt_indata.rem[key]
                         if opt_rem.get(key, None) != opt_indata.rem[key]:
@@ -365,7 +365,7 @@ def opt_with_frequency_flattener(
                 freq_outdata = QCOutput(output_file + ".freq_" + str(ii)).data
                 freq_indata = QCInput.from_file(input_file + ".freq_" + str(ii))
                 for key in freq_indata.rem:
-                    if key not in ["job_type", "geom_opt2", "scf_guess_always"]:
+                    if key not in {"job_type", "geom_opt2", "scf_guess_always"}:
                         if freq_rem.get(key, None) != freq_indata.rem[key]:
                             freq_rem[key] = freq_indata.rem[key]
                         if opt_rem.get(key, None) != freq_indata.rem[key] and key != "cpscf_nseg":

custodian/vasp/handlers.py

@@ -246,7 +246,7 @@ def correct(self):
                 self.error_count["brmix"] += 1
 
             elif (
-                self.error_count["brmix"] in [2, 3]
+                self.error_count["brmix"] in {2, 3}
                 and vi["KPOINTS"]
                 and vi["KPOINTS"].style == Kpoints.supported_modes.Monkhorst
             ):
@@ -264,7 +264,7 @@ def correct(self):
                         }
                     )
 
-            elif self.error_count["brmix"] in [2, 3] and vi["INCAR"].get("KSPACING"):
+            elif self.error_count["brmix"] in {2, 3} and vi["INCAR"].get("KSPACING"):
                 actions.append({"dict": "INCAR", "action": {"_set": {"KGAMMA": True}}})
 
             else:
@@ -476,7 +476,7 @@ def correct(self):
                 is_contcar = False
             if is_contcar:
                 actions.append({"file": "CONTCAR", "action": {"_file_copy": {"dest": "POSCAR"}}})
-            if vi["INCAR"].get("ALGO", "Normal").lower() in ["fast", "veryfast"]:
+            if vi["INCAR"].get("ALGO", "Normal").lower() in {"fast", "veryfast"}:
                 actions.append({"dict": "INCAR", "action": {"_set": {"ALGO": "Normal"}}})
             else:
                 potim = round(vi["INCAR"].get("POTIM", 0.5) / 2.0, 2)
@@ -525,7 +525,7 @@ def correct(self):
             # are often used with ALGO = All (and hybrids are incompatible with ALGO = VeryFast/Fast and slow with
             # ALGO = Normal), we do not adjust ALGO in these cases.
             if vi["INCAR"].get("METAGGA", "none") == "none" and not vi["INCAR"].get("LHFCALC", False):
-                if vi["INCAR"].get("ALGO", "Normal").lower() in ["all", "damped"]:
+                if vi["INCAR"].get("ALGO", "Normal").lower() in {"all", "damped"}:
                     actions.append({"dict": "INCAR", "action": {"_set": {"ALGO": "Fast"}}})
                 elif 53 <= vi["INCAR"].get("IALGO", 38) <= 58:
                     actions.append({"dict": "INCAR", "action": {"_set": {"ALGO": "Fast"}, "_unset": {"IALGO": 38}}})
@@ -636,7 +636,7 @@ def correct(self):
             # 2) Use ALGO = Damped but only *after* an ISMEAR = 0 run where the wavefunction
             # has been stored and read in for the subsequent run.
             if (
-                (algo in ["all", "damped"] or (50 <= vi["INCAR"].get("IALGO", 38) <= 59))
+                (algo in {"all", "damped"} or (50 <= vi["INCAR"].get("IALGO", 38) <= 59))
                 and vi["INCAR"].get("ISMEAR", 1) < 0
                 and self.error_count["algo_tet"] == 0
             ):
@@ -1445,7 +1445,7 @@ def correct(self):
 
         # NOTE: This is the algo_tet handler response.
         if (
-            incar.get("ALGO", "Normal").lower() in ["all", "damped"] or (50 <= incar.get("IALGO", 38) <= 59)
+            incar.get("ALGO", "Normal").lower() in {"all", "damped"} or (50 <= incar.get("IALGO", 38) <= 59)
         ) and incar.get("ISMEAR", 1) < 0:
             # ALGO=All/Damped / IALGO=5X often fails with ISMEAR < 0. There are two options VASP
             # suggests: 1) Use ISMEAR = 0 (and a small sigma) to get the SCF to converge.
@@ -1773,7 +1773,7 @@ def correct(self):
         # change ALGO = Fast to Normal if ALGO is !Normal
         vi = VaspInput.from_directory(".")
         algo = vi["INCAR"].get("ALGO", "Normal").lower()
-        if algo not in ["normal", "n"]:
+        if algo not in {"normal", "n"}:
             backup(VASP_BACKUP_FILES)
             actions = [{"dict": "INCAR", "action": {"_set": {"ALGO": "Normal"}}}]
             VaspModder(vi=vi).apply_actions(actions)

custodian/vasp/jobs.py

@@ -186,7 +186,7 @@ def setup(self):
                 incar = Incar.from_file("INCAR")
                 # Only optimized NPAR for non-HF and non-RPA calculations.
                 if not (incar.get("LHFCALC") or incar.get("LRPA") or incar.get("LEPSILON")):
-                    if incar.get("IBRION") in [5, 6, 7, 8]:
+                    if incar.get("IBRION") in {5, 6, 7, 8}:
                         # NPAR should not be set for Hessian matrix
                         # calculations, whether in DFPT or otherwise.
                         del incar["NPAR"]
@@ -361,7 +361,7 @@ def metagga_opt_run(
         auto_continue=False,
     ):
         """
-        Returns a list of thres jobs to perform an optimization for any
+        Returns a list of three jobs to perform an optimization for any
         metaGGA functional. There is an initial calculation of the
         GGA wavefunction which is fed into the initial metaGGA optimization
         to precondition the electronic structure optimizer. The metaGGA
@@ -372,7 +372,7 @@ def metagga_opt_run(
         metaGGA = incar.get("METAGGA", "SCAN")
 
         # Pre optimize WAVECAR and structure using regular GGA
-        pre_opt_setings = [
+        pre_opt_settings = [
             {
                 "dict": "INCAR",
                 "action": {"_set": {"METAGGA": None, "LWAVE": True, "NSW": 0}},
@@ -384,7 +384,7 @@ def metagga_opt_run(
                 auto_npar=auto_npar,
                 final=False,
                 suffix=".precondition",
-                settings_override=pre_opt_setings,
+                settings_override=pre_opt_settings,
             )
         ]
 

custodian/vasp/validators.py

@@ -117,7 +117,7 @@ def check_broken_chgcar(chgcar, diff_thresh=None):
     Args:
         chgcar (Chgcar): Chgcar-like object.
         diff_thresh (Float): Threshold for diagonal difference.
-                        None means we won't check for this.
+            None means we won't check for this.
     """
     chgcar_data = chgcar.data["total"]
     if (chgcar_data < 0).sum() > 100: